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A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization | |
Woldu, Tsegay Giday1; Zhang, Haibin1; Zhang, Xin2; Fissuh, Yemane Hailu1 | |
发表期刊 | JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
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ISSN | 0022-3239 |
2020-02-12 | |
页码 | 16 |
通讯作者 | Woldu, Tsegay Giday(tsegikuhil@gmail.com) |
摘要 | Nonlinear conjugate gradient methods are among the most preferable and effortless methods to solve smooth optimization problems. Due to their clarity and low memory requirements, they are more desirable for solving large-scale smooth problems. Conjugate gradient methods make use of gradient and the previous direction information to determine the next search direction, and they require no numerical linear algebra. However, the utility of nonlinear conjugate gradient methods has not been widely employed in solving nonsmooth optimization problems. In this paper, a modified nonlinear conjugate gradient method, which achieves the global convergence property and numerical efficiency, is proposed to solve large-scale nonsmooth convex problems. The new method owns the search direction, which generates sufficient descent property and belongs to a trust region. Under some suitable conditions, the global convergence of the proposed algorithm is analyzed for nonsmooth convex problems. The numerical efficiency of the proposed algorithm is tested and compared with some existing methods on some large-scale nonsmooth academic test problems. The numerical results show that the new algorithm has a very good performance in solving large-scale nonsmooth problems. |
关键词 | Conjugate gradient method Moreau-Yosida regularization Nonsmooth large-scale problems Global convergence |
DOI | 10.1007/s10957-020-01636-7 |
关键词[WOS] | NONMONOTONE LINE SEARCH ; CONVERGENCE ANALYSIS ; BUNDLE METHODS ; SEGMENTATION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[11771003] ; National Natural Science Foundation of China[11771003] |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Operations Research & Management Science ; Mathematics |
WOS类目 | Operations Research & Management Science ; Mathematics, Applied |
WOS记录号 | WOS:000513025700002 |
出版者 | SPRINGER/PLENUM PUBLISHERS |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/28565 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Woldu, Tsegay Giday |
作者单位 | 1.Beijing Univ Technol, Coll Appl Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Woldu, Tsegay Giday,Zhang, Haibin,Zhang, Xin,et al. A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization[J]. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS,2020:16. |
APA | Woldu, Tsegay Giday,Zhang, Haibin,Zhang, Xin,&Fissuh, Yemane Hailu.(2020).A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization.JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS,16. |
MLA | Woldu, Tsegay Giday,et al."A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization".JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS (2020):16. |
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